时间：六月一日上午10时
地点：教七102室
报告人：Yanxi Liu

Machine Learning for Computational Regularity
-- Symmetry Discovery from Real World Patterns

We explore a formal and computational characterization of real world
regularity using discrete symmetry groups (hierarchy) as a theoretical
basis, embedded in a well-defined Bayesian framework. Our existing work
on ‘Near-regular texture analysis and manipulation’ (SIGGRAPH 2004) and
“A Lattice-based MRF Model for Dynamic Near-regular Texture Tracking”
(TPAMI 2007) already demonstrate the power of such a formalization on a
diverse set of real problems, such as texture analysis, synthesis,
tracking, perception and manipulation in terms of regularity. Symmetry
and symmetry group detection from real world data turns out to be a very
challenging problem that has been puzzling computer vision researchers
for the past 40 years (CVPR 2008). Our novel formalization will lead the
way to a more robust and comprehensive algorithmic treatment of the
whole regularity spectrum, from regular (perfect symmetry), near-regular
(approximate symmetry), to various types of irregularities. The proposed
method will be justified by several real world applications in computer
vision, computer graphics and biomedical image analysis applications
such as deformed lattice detection and tracking (PAMI 2009), gait
recognition (ECCV2002,CVPR2007), grid-cell clustering (Neurocomputing
2007), symmetry of dance (SIGGRAPH ASIA 2009), automatic geo-tagging
(CVPR2008), shape matching and retrieval (ICCV 2009), and image
de-fencing (CVPR2008,ICCV2009).

BIO:

Yanxi Liu received her BS in physics/electrical engineering (Beijing, China), her Ph.D. degree in computer science for group theor y applications in robotics from University of Massachusetts (Amherst, MA, US) and her postdoctoral training at LIFIA/IMAG (Grenobe, France). She also spent one year at DIMACS (NSF center for Discrete Mathematics and Theoretical Computer Science) with an NSF research-education fellowship award. Dr. Liu was a research associate professor in the Robotics Institute of Carnegie
Mellon University before she joined the Computer Science Engineering
and Electrical Engineering depar tments of Penn State University in Fall
of 2006 as a tenured faculty and the co-director of the lab for perception,
action and cognition (LPAC). Dr. Liu’s research interests and publications span a wide range of applications including computer vision, computer graphics, robotics, human perception and computer aided diagnosis in medicine, with a theme on computational and theoretical symmety/regularity. Dr. Liu chaired the First International Workshop on Computer Vision for Biomedical Image Applications (CVBIA) in Beijing, and edited the book on ”CVBIA: Current Techniques and Future Trends” (Springer-Verlag LNCS). She served
as a multi-year chartered study section member for NIH (Biomedical Computing and Health Informatics), and recently served as an area chair/organizing committee member for CVPR08/MICCAI08/CVPR09.
Dr. Liu is a senior member of IEEE and the IEEE Computer Society.